Wireless Sensor Network (WSN) enables pervasive, ubiquitous, and seamless communication with the physical world. This paper investigates an optimal cross-layer joint routing and scheduling problem ...for WSN with periodic data collection. The problem is formulated as an Integer Linear Program (ILP) model such that a joint scheduling and routing is developed to maximize network lifetime and minimize delay. In this paper, an ILP model with multi objective cost function is proposed. The proposed ILP model represents the operation of Energy-Efficient Distributed Schedule-Based (EEDS) protocol. The ILP model is solved for different network configurations. The optimal solutions assuming different objectives are compared.
Growing Unmanned Aerial Vehicle (UAV) market trends and interest in potential uses such as monitoring, visual inspection, object detection, and path planning have shown promising results using ...machine learning techniques. However, UAV adoption faces several challenges in real-life scenarios as lowaccuracy sensors are involved in the identification, tracking, and localization of UAVs. In order to overcome the aforementioned challenges, this paper proposes an intelligent machine learningbased system coupled with computer vision (CV) to detect objects and localize UAVs equipped with just a monocular camera. The experimental results using the Telo DJI drone demonstrate that the proposed methodology can detect, track objects, and localize the drone with high accuracy. The system's ability for automated monitoring in real environments can lend its uses for urban traffic, logistics, and security applications.
Wireless sensor networks can provide effective means for monitoring and controlling a wide range of applications. Recently, tremendous effort was directed towards devising sensors powered from ...ambient sources such as heat, wind, and vibration. Wireless energy transfer is another source that has attractive features that make it a promising candidate for supplying power to wireless sensor nodes. This paper is concerned with characterizing and modeling the charging time and received signal strength indicator for wireless energy transfer system. These parameters play a vital role in deciding the geometry of sensor network and the routing protocols to be deployed. The development of communication protocols for wireless-powered wireless sensor networks is also improved with the knowledge of such models. These two quantities were computed from data acquired at various coordinates of the harvester relative to a fixed position of RF energy source. Data was acquired for indoor and outdoor scenarios using the commercially available PowerCast energy harvester and evaluation board. Mathematical models for both indoor and outdoor environments were developed and analyzed. A few guidelines on how to use these models were suggested. Finally, the possibility of harvesting the energy from the ambient RF power to energize wireless sensor nodes was also investigated.
Federated Learning (FL) is a cooperative machine learning (ML) training method that involves several participants in the training phase. The learning phase of ML algorithms is done in a distributed ...manner where devices train a specific model based on their local data sets and send the updated model back to a centralized entity. Several benefits are gained by using FL compared to conventional centralized learning techniques, such as increased security and data privacy since participant devices only send back the updated model and not their data sets. Recently, this has become a hot research topic due to its advantages in terms of user privacy. Most of the works in this field consider only star networks where mobile devices communicate directly to the base station. Few mentioned multi-hop scenarios. In this paper, we present a performance evaluation of FL in multi-hop networks and study the effect of clustering devices on FL accuracy.
WSN Routing Protocols: Anonymity Prospective Analysis Elkhail, Abdulrahman Abu; Baroudi, Uthman; Younis, Mohammed
2022 14th International Conference on Computational Intelligence and Communication Networks (CICN),
2022-Dec.-4
Conference Proceeding
A Wireless Sensor Network (WSN) is composed of a number of sensor nodes and a single Base-Station (BS), distributed randomly in an area of interest. WSNs have proven very beneficial in various ...applications in unattended setup in many domains such as scientific, civil, and military. In these applications, sensors send their measurements to the Base Station over multi-hop wireless routes where the Base Station is responsible for collecting and processing the sensed data. Given the importance of the BS, a potential attacker would look to locate the base station by examining network traffic patterns in order to launch specific attacks intended to interfere with network functionality. In this paper, we analyze traffic analysis attack models from the viewpoint of an adversary. Additionally, we examine the benefits and drawbacks of various routing protocols in terms of exposing the network to traffic analysis attacks. Our evaluation is supported by simulation results.
In Wireless Sensor-Actor Networks (WSANs), actors collect sensor readings and respond collaboratively to achieve an application mission. Since actors coordinate their operation, a strongly connected ...network topology would be required at all time. In addition, the path between actors may have to be capped in order to meet latency constraints. However, a failure of an actor may cause the network to partition into disjoint blocks and would thus violate such connectivity goal. One of the effective recovery methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary schemes rely on maintaining 1 or 2-hop neighbor lists and predetermine criteria for node's involvement in the recovery. However, 1-hop based schemes often impose high node relocation overhead. In addition, the repaired inter-actor topology using 2-hop schemes often differs significantly from its pre-failure status and some inter-actor data paths may get extended. This paper presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies on the local view of a node about the network in order to devise a recovery plan that relocates the least number of nodes and ensures that no path between any pair of nodes is extended. LeDiR is a localized and distributed algorithm that leverages existing path discovery activities and imposes no additional pre-failure communication overhead. LeDiR is validated through simulation and is shown to outperform existing schemes.
The technological advances in smartphones have brought promising potentials to tracking systems. GPS and WLAN are widely used technologies in recent smartphones for positioning and communication, ...respectively. However, both GPS and WLAN have serious energy consumption problem. For large scale tracking systems, where tracked people are supposed to move in groups, the continuous usage of the individual smartphones GPS and WiFi is not an energy efficient solution. In this work, we propose a cooperative approach that exploits the coexistence of of multiple communication interfaces (WiFi and Bluetooth) in recent smartphones where nearby smartphones are cooperatively grouped to form a cluster. A cluster is a network of one dynamically selected cluster head and regular members that communicate locally via Bluetooth. The cluster head is responsible of positioning and sharing positioning information with the rest of cluster members. It, also, acts as a gateway between its regular members and the server. We present a clustering approach according to the available energy and the energy cost. Our approach doesnt require any modifications in the recent smartphones equipment. We have formulated the clustering construction problem as a mixed integer program using GAMS. The proposed clustering approach has been evaluated via extensive simulation experiments and the obtained results have been compared with the optimal solution which show very close performance.
In many applications, robots autonomous deployment is preferable and sometimes it is the only affordable solution. To address this issue, virtual force (VF) is one of the prominent approaches to ...performing multirobot deployment autonomously. However, most of the existing VF-based approaches consider only a uniform deployment to maximize the covered area while ignoring the criticality of specific locations during the deployment process. To overcome these limitations, we present a framework for autonomously deploy robots or vehicles using virtual force. The framework is composed of two stages. In the first stage, a two-hop Cooperative Virtual Force based Robots Deployment (Two-hop COVER) is employed where a cooperative relation between robots and neighboring landmarks is established to satisfy mission requirements. The second stage complements the first stage and ensures perfect demand satisfaction by utilizing the Trace Fingerprint technique which collected traces while each robot traversing the deployment area. Finally, a fairness-aware version of Two-hop COVER is presented to consider scenarios where the mission requirements are greater than the available resources (i.e. robots). We evaluate our framework via extensive simulations. The results demonstrate outstanding performance compared to contemporary approaches in terms of total travelled distance, total exchanged messages, total deployment time, and Jain fairness index.
One of the most significant challenges in wide-scale Wireless Sensor Networks (WSNs) is to achieve energy efficiency in order to increase their lifetime and ensuring responsiveness. A very widely ...applied approach in this regard is to overload the region with numerous low-cost sensing devices that can communicate with each other wirelessly and coordinate amongst themselves in developing schedules for being asleep or active. The literature has numerous research works in this regard which aim to develop efficient sleep scheduling schemes. In this paper, we present an implementation of a grid-topology based cooperative Rank Based Sleep Scheduling (RBSS) protocol in which the nodes of every cell coordinate in a distributive manner, the decision making process of selecting the nodes that should stay active, while others sleep. The proposed protocol guarantees the WSN connectivity as well as the required coverage. Finally, we implement RBSS on a small scale grid using TelosB motes.
The time sensitivity of healthcare applications leads to the urgent need to process the data with minimum delay. The limited resources in end-user devices make offloading the tasks to the fog node to ...process them essential. Fog node can process the tasks near the end-user, which reduce the delay caused by offloading them into the cloud. Fog nodes in the fog layer can collaborate to process tasks. A balanced task schedule in the fog layer will make the fog nodes collaborate to reduce the response time. In this work, we start by computing a probability for each task to decide whether the task will offload to the fog master or not. This probability will allow the fog node to process some of the received tasks without the need for offloading. We only offload the tasks whose probability exceeds a threshold value to the fog master. The fog master run the Ant Colony Optimization algorithm to schedule the task to a suitable node in the fog layer. The simulation results show that the proposed load balancer provides better results in reducing the delay.
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